Efficient Coalitions Research Articles

Coalition Formation among the Cooperative Agents for Efficient Energy Consumption

Energy saving is a significant research area in Saudi Arabia; however, significant problems have emerged related to its distribution and consumption. Use of an agent is assumed to combat these problems by forming efficient coalitions to control the energy consumption and energy distribution process. This study presents a novel algorithm for distributing the value calculation among the cooperative agents. This is likely to reduce the consumption of energy and extend the coalition lifetime used. The developed algorithm is compared with the basic modified coalition formation algorithm for evaluating its effectiveness. The results showed a reduction in cooling consumption by 20% after applying optimization algorithms. The amount of reduction in the cooling consumption reflects a 31% reduction in expected cooling costs, without affecting the household comfort. Therefore, the study concludes that DNsys provided better performance than the NNsys.

A Combined Traffic and Workload-aware Optimized Virtual Machine Migration in Cloud Computing

In cloud computing paradigm, Virtual Machine (VM) migration strategies play a vital role in reducing the Energy Consumption (EC) and balancing the workloads in the cloud servers. From this viewpoint, an Osmotic Hybrid artificial Bee and Ant Colony with Future Utilization Prediction and Multipath Traffic Routing (OH-BAC-FUP-MTR) strategy was designed to accomplish effective load-balancing and minimize the chance of traffic congestion during VM migration in data centres. But, the tradeoffs among workload efficiency and power-gain in heterogeneous cloud servers were not analyzed. Hence in this article, a VM consolidation strategy is proposed with OH-BAC-FUP-MTR to switch the idle Physical Machines (PMs) into hibernation mode, resulting in very less EC. In this strategy, the VM migration is targeted at consolidating the VMs depending on the workload to the smaller number of PMs for reducing the power use and encouraging green computing. Initially, the PMs are split into various groups depending on their workload levels and then a new Merge-and-Split-based Coalitional Game-theoretic (MSCG) method is applied to select associates from these groups to create efficient coalitions. After that, OH-BAC-FUP-MTR is performed amongst the coalition associate for maximizing the reward of each coalition and PMs are maintained to operate in the maximum power-efficient condition. Finally, the investigational outcomes exhibit the OH-BAC-FUP-MTR-MSCG achieves a mean EC of 60.63KWh which is 28.87% less than all other classical VM migration strategies.

Cultural coalitions detection approach using GPU based on hybrid Bat and Cultural Algorithms

Currently, robot technology plays a crucial role in our modern life. Its great favor over humanity was not limited to the industrial domain, but also on the social one. Social robots become equipped with an artificial culture that allows them to interact with humans. Although the great importance of this technology, some misdeeds can create a real catastrophe. Coalition creation is one of its most dangerous troubles, where a subset of robots cooperates to impose pernicious decisions. There are efficient coalitions detection methods, but their exponential computation time makes their use limited only to small data. This paper is an extended version of Kechid and Drias (2019) presented at the IEA/AIE 2019 conference. In this paper, we propose a Cultural coalitions detection approach using GPU based on hybrid Bat and Cultural Algorithms. Unlike the existing literature, We view the problem of finding coalitions as an optimization problem to get relevant solutions in a significantly reduced amount of time. The proposed approach can increase the population diversity and improve the searching ability for an optimal exploration–exploitation balance. Also, it can launch several cultural bats in GPU to make real parallelism. Experimental results on several datasets show that the proposed method will considerably reduce the runtime. These datasets represent the result of artificial cultural agents playing the colored trails (CT) game. Concerning the creation of profiles, we use real datasets generated based on the World Values survey.

Using system dynamics modeling to evaluate a community-based social marketing framework

PurposeCommunity coalitions are an important part of the public milieu and subject to similar external pressures as other publicly funded organizations – including changes in required strategic orientation. Many US government agencies that fund efforts such as community-based social marketing initiatives have shifted their funding agenda from program development to policy development. The Florida Prevention Research Center at the University of South Florida (Tampa, Florida, USA) created community-based prevention marketing (CBPM) for policy development framework to teach community coalitions how to apply social marketing to policy development. This paper aims to explicate the framework’s theory of change.Design/methodology/approachThe research question was: “How does implementing the CBPM for Policy Development framework improve coalition performance over time?” The authors implemented a case study design, with the “case” being a normative community coalition. The study adhered to a well-developed series of steps for system dynamics modeling.FindingsResults from computer model simulations show that gains in community coalition performance depend on a coalition’s initial culture and initial efficiency, and that only the most efficient coalitions’ performance might improve from implementing the CBPM framework.Originality/valuePractical implications for CBPM’s developers and users are discussed, namely, the importance of managing the early expectations of academic-community partnerships seeking to shift their orientation from downstream (e.g. program development) to upstream social marketing strategies (e.g. policy change).

Use of a quantum genetic algorithm for coalition formation in large-scale UAV networks

Task allocation among a network of heterogeneous resource-constrained Unmanned Aerial Vehicles (UAVs) in an unknown and remote environment is still a challenging problem noting the limited available information about highly dynamic environment, lack of continuous and reliable communication network, and the limited energy and resources available at the UAVs. One solution for this such allocation problem is to form several efficient coalitions of the UAVs, where a complex task is assigned to a group of agents (i.e., a coalition) carrying the required resources/capabilities to perform this task. In this paper, inspired by Quantum Evolutionary Algorithms, we propose a leader-follower coalition formation algorithm in a large-scale UAV network to form the best possible coalitions of agents to accomplish the detected tasks in an unknown environment. Three main objectives have been considered in this coalition formation: (i) minimizing resource consumption in completing the assigned tasks on time; (ii) enhancing the reliability of the coalitions; and (iii) considering the most trustworthy UAVs amid the self-interested UAVs in forming the coalitions. The simulation results demonstrate the superior performances of the proposed model in different scenarios with large number of UAVs compared to existing coalition formation algorithms such as merge-and-split and a famous multi-objective genetic algorithm called NSGA-II.11DISTRIBUTION A. Approved for public release: distribution unlimited. Case Number: 88ABW-2018-0096. Dated 10 Jan 2018.22An earlier version of this work was presented at 2018 INFOCOM Workshop on WISARN: Wireless Sensor, Robot and UAV Networks, Honolulu, HI.

Walking Through the Sahrawi Refugee Camps with Judith Butler

This article considers the role that irredentist nationalist Moroccan and Sahrawi discourses have played in the current stalemate in the negotiations in the Western Sahara conflict. Despite this, Morocco has seen a series of revolutionary and reformist movements prior to and in the wake of the 2010 Arab Spring. Although these movements have often been outmaneuvered by the Moroccan monarchy, they have managed to force a realignment of forces as exemplified by the Moroccan 2011 Constitution. I draw on Judith Butler’s critique of identitarian discourses to suggest that women’s rights may be a productive platform for Sahrawi women to establish equally efficient coalitions with other women in Morocco, and work to break the current stalemate.

Efficient Formulas and Computational Efficiency for Glove Games

A well known and simple game to model markets is the glove game where worth is produced by building matching pairs. For glove games, different concepts, like the Shapley value, the restricted Shapley value or the Owen value, yield different distributions of worth. Moreover, computational effort of these values is in general very high. This paper provides efficient allocation formulas of the component restricted Shapley value and the Owen value for glove games in case of efficient coalitions.

Intelligent Algorithm for Assignment of Agents to Human Strategy in Centralized Multi-agent Coordination

Problem: Multi-agent coordination is an important issue in the domain of disaster emergency response operations where a team of agents (field units or robots) aims to achieve a joint objective. The responsibility of the Incident Commander (IC) is to (I) specify an effective strategy composed of a number of threads (a set of prioritized sub-problems), (II) appropriately assign/allocate agents to these threads as a strategic decision, and (III) release agents in a timely manner from the assigned threads to adapt a strategic decision to a new situation. Objective: The purpose of this paper is to present an intelligent algorithm that assists a human in multi-agent coordination by providing two key functions: 1) automatically calculate and present a set of feasible alternatives for selecting a choice as a strategic decision in a definite time, and 2) autonomously and in a timely manner identify a subset of assigned agents that should be released from their threads in order to refine a strategic decision. Method: This algorithm expands a decision tree from a state node in which a thread (or several threads) has received a set of new agents from either the IC or a higher thread. Each thread is associated with one level of a decision tree with a number of nodes. A thread calculates a set of efficient coalitions using all the available agents and generates a new node for each coalition to show what agents are allocated to the thread and what agents are released into a lower thread. In real-time, this algorithm continuously observes and monitors the task environment to identify a subset of the assigned agents that cannot provide efficient capabilities for their threads and should be released for assignment to other threads. Results: To gather further insight, this paper applied this algorithm for team coordination to a simulated search & rescue scenario in an earthquake disaster-affected area where the team's goal was to rescue trapped people distributed in five operational zones. The result was an infinite set of alternative scenarios for a human-defined strategy. The calculated alternatives were presented to the IC for selection according to his intuition or for delegation to the system to determine an optimal strategy.

Cooperative games and multiagent systems

AbstractForming coalitions is a generic means for cooperation: people, robots, web services, resources, firms; they can all improve their performance by joining forces. The use of coalitions has been successful in domains such as task allocations, sensor networks, and electronic marketplaces. Forming efficient coalitions requires the identification of matching synergies between different entities (finding complementary partners, or similar partners, or partners who add diversity). In addition, the different parties must negotiate a fair repartition of the worth created by the coalition. The first part of this paper is a tutorial on cooperative game theory (also called coalitional games). We then survey the different scenarios and the key issues addressed by the multiagent systems community.

Coalition Formation and Cost Allocation for Joint Replenishment Systems

This paper focuses on the issues of coalition formation and cost allocation in a joint replenishment system involving a set of independent and freely interacting retailers purchasing an item from one supplier to meet a deterministic demand. The papers dealing with this problem are mainly focused on supperadditive games, where the cost savings associated with a coalition increase with the number of players in the coalition. The most relevant question addressed then is how to allocate the savings to the players. In this paper, we propose to go further by dealing with a non‐supperadditive game, where a set of independent retailers have the common understanding to share the cost savings according to the cost‐based proportional rule. In this setting, the global cost optimization is no longer a relevant approach to identify appealing coalitions for any retailer. Here, we provide an iterative procedure to form the so‐called efficient coalition structure and we show that this coalition structure has the nice properties of being (i) weakly stable in the sense of the coalition structure core and (ii) strongly stable under a given assumption. An exact fractional programming based solution is also given to generate such efficient coalitions.

Effectivity functions and efficient coalitions in Boolean games

Boolean games are a logical setting for representing strategic games in a succinct way, taking advantage of the expressive power and conciseness of propositional logic. A Boolean game consists of a set of players, each of which controls a set of propositional variables and has a specific goal expressed by a propositional formula. We show here that Boolean games are a very simple setting, yet sophisticated enough, for analysing the formation of coalitions. Due to the fact that players have dichotomous preferences, the following notion emerges naturally: a coalition in a Boolean game is efficient if it has the power to guarantee that all goals of the members of the coalition are satisfied. We study the properties of efficient coalitions.

How do coalitions get built? Evidence from an extensive form coalition game with and without communication

In the laboratory, we investigate a non-cooperative three-person coalition game with externalities and the opportunity to extend existing coalitions. One bargainer, the builder, can propose and build a coalition over two stages. We examine the hypothesis that both absolute and relative payoffs affect the coalition formation process (and outcome). We observe many inefficient two-person final coalitions, and that the distribution of outcomes is sensitive to the constellation of both absolute and relative payoffs. Relative payoffs appear to be applied more myopically than has been observed in bilateral sequential bargaining games or suggested by social preference models. We hypothesize that the prevalence of two-person coalitions stems from builder’s uncertainty about individual acceptance thresholds. In fact, allowing nonbinding communication among the bargainers increases the prevalence of efficient coalitions. The main implication is that efficient coalition building involves strategies for mitigating the strategic uncertainty inherent in building coalitions.

The Endogenous Formation of Coalitions to Provide Public Goods: Theory and Experimental Evidence

This paper examines the endogenous formation of coalitions that provide public goods in which players implement a minimum participation requirement before deciding whether to join. We demonstrate theoretically that payoff-maximizing players will vote to implement efficient participation requirements and these coalitions will form. However, we also demonstrate that if some players are averse to inequality they can cause inefficient outcomes. Inequality-averse players can limit free riding by implementing larger than efficient coalitions or by blocking efficient coalitions from forming. We test the theory with experimental methods and observe individual behavior and coalition formation consistent with a model of inequality-averse players.